A Novel Anti-CEACAM5 Monoclonal Antibody, CC4, Suppresses Colorectal Tumor Growth and Enhances NK Cells-Mediated Tumor Immunity

Carcinoembryonic antigen (CEA, CEACAM5, and CD66e) has been found to be associated with various types of cancers, particularly colorectal carcinoma, and developed to be a molecular target for cancer diagnosis and therapy. In present study, we generated a novel anti-CEACAM5 monoclonal antibody, namely mAb CC4, by immunizing mice with living colorectal cancer LS174T cells. Immunohistochemical studies found that mAb CC4 specifically and strongly binds to tumor tissues, especially colorectal adenocarcinoma. In xenografted mice, mAb CC4 is specifically accumulated in tumor site and remarkably represses colorectal tumor growth. In vitro functional analysis showed that mAb CC4 significantly suppresses cell proliferation, migration and aggregation of colorectal cancer cells and also raises strong ADCC reaction. More interestingly, mAb CC4 is able to enhance NK cytotoxicity against MHC-I-deficient colorectal cancer cells by blocking intercellular interaction between epithelial CEACAM5 and NK inhibitory receptor CEACAM1. These data suggest that mAb CC4 has the potential to be developed as a novel tumor-targeting carrier and cancer therapeutic

Interval-valued Evidence Updating with Reliability and Sensitivity Analysis for Fault Diagnosis

Information fusion methods based on Dempster-Shafer evidence theory (DST) have been widely used in fault diagnosis. In DST-based methods, the monitoring information collected from sensors is modeled as multiple pieces of diagnosis evidence in the form of basic belief assignment (BBA), and Dempster’s rule is then used to combine these BBAs to obtain the fused BBA for diagnosis decision making. However, the belief structure with crisp singlevalued belief degrees in BBA may be too coarse to truthfully represent detailed fault information. Moreover, Dempster’s rule only uses a static combination process, which is unsuitable for dynamically fusing information collected at different time steps. In order to address these issues, the paper proposes a dynamic diagnosis method based on interval-valued evidential updating. First of all, the diagnosis evidence is constructed as an interval-valued belief structure (IBS), which provides a more informative scheme than BBA to model fault information. Secondly, the proposed evidential updating strategy can generate updated IBS as global diagnosis evidence by updating the previous evidence with the new incoming evidence recursively. Thirdly, the reliability and sensitivity indices are designed to evaluate and compare the performance of the proposed updating strategy with other commonly used strategies. Finally, the effectiveness of the proposed evidential updating strategy is demonstrated through some typical fault experiments of a machine rotor

CLINICAL ANALYSIS OF ASSOCIATION OF CYSTATIN C AND ATRIAL FIBRILLATION

Some studies have disclosed atrial fibrillation (AF) is associated with inflammation. Cystatin C is not only inflammatory markers but also an independent predictor of cardiovascular events.Aim. We sought to investigate the relationship between serum levels of cystatin C and the occurrence and development of AF.Material and methods. 134 paroxysmal and persistent AF (AF1 group) and 121 permanent AF (AF2 group) patients in AF group and 154 healthy people in control group were prospectively measured for cystatin C, other inflammatory markers, biochemical indicators, left atrial diameter (LAD), left ventricular diameter (LVD) and left ventricular ejection fraction (LVEF).Results. (1) Compared with control and AF1 groups, AF2 group had higher values of cystatin C, high sensitivity C reactive protein (hsCRP), LAD and LVD whereas lower values of LVEF (P<0.05). (2) After adjust for age, gender and body mass index (BMI), correlation analysis showed that serum level of cystatin C was closely related to hsCRP, LAD, systolic blood pressure (SBP) and creatinine, the correlation coefficient were respectively 0.658, 0.502, 0.475 and 0.530 (P<0.01), but negatively associated with LVEF (P=0.011) in AF group. (3) Multivariate regression analysis showed the hsCRP, cystatin C, LAD and LVEF entered finally into the regression equation (cystatin C, OR: 3.41, 95%CI: 1.09–11.08, P=0.009).Conclusion. The serum levels of cystatin C has significant correlation with AF, which indicates cystatin C may play an important role in the process of AF development

Will Delayed Retirement Affect the Health of Chinese Workers? A Study from the Perspective of Sustainability of Physical Health

This article presents the important research findings of our study on whether delayed retirement will affect the health of Chinese workers from the perspective of sustainability of physical health. The treatment group is those who continue to work after the current statutory retirement age and the control group are those who no longer work after current statutory retirement age, and the physical health of these people is used as a dependent variable. The samples are selected from the following six regions of China: Shanghai, Chengdu, Guangzhou, Beijing, Zhengzhou, and Shenyang. Quantitative studies of physical health status of the samples are carried out. The study illustrates that for female manual workers who are younger than 63 years old, female non-manual workers who are younger than 66 years old, male manual workers who are younger than 64 years old, and male non-manual workers who are younger than 67 years old, delaying retirement, and continuing to stay in work has no effect on their physical health. After these chronological age stages, however, it has significant impact on their health. These research findings have significant impact and value for the design of China’s delayed retirement policy

CLINICAL ANALYSIS OF ASSOCIATION OF CYSTATIN C AND ATRIAL FIBRILLATION

Some studies have disclosed atrial fibrillation (AF) is associated with inflammation. Cystatin C is not only inflammatory markers but also an independent predictor of cardiovascular events.Aim. We sought to investigate the relationship between serum levels of cystatin C and the occurrence and development of AF.Material and methods. 235 paroxysmal and persistent AF (AF1 group) and 254 permanent AF (AF2 group) patients in AF group and 221 healthy people in control group were prospectively measured for cystatin C, other inflammatory markers, biochemical indicators, left atrial diameter (LAD), left ventricular diameter (LVD) and left ventricular ejection fraction (LVEF).Results. (1) Compared with control and AF1 groups, AF2 group had higher values of cystatin C, high sensitivity C reactive protein (hsCRP), LAD and LVD whereas lower values of LVEF (P<0.05). (2) After adjust for age, gender and body mass index (BMI), correlation analysis showed that serum level of cystatin C was closely related to hsCRP, LAD, systolic blood pressure (SBP) and creatinine, the correlation coefficient were respectively 0,614, 0,520, 0,463 and 0,538 (all P<0,01), but negatively associated with LVEF (r= –0,356, P=0,012) in AF group. (3) Multivariate regression analysis showed the hsCRP, cystatin C, LAD and LVEF entered finally into the regression equation (cystatin C, OR: 3.25, 95%CI: 1.05–10.17, P=0,008).Conclusion. The serum levels of cystatin C has significant correlation with AF, which indicates cystatin C may play an important role in the process of AF development

Real-time topology optimization based on convolutional neural network by using retrain skill

To realize a real-time structural topology optimization (TO), it is essential to use the information during the TO process. A step-to-step training method is proposed to improve the deep learning model prediction accuracy based on the solid isotropic material with penalization (SIMP) TO method. By increasing the use of optimization history information (such as the structure density matrix), the step-to-step method improves the model utilization efficiency for each sample data. This training method can effectively improve the deep learning model prediction accuracy without increasing the sample set size. The step-to-step training method combines several independent deep learning models (sub-models). The sub-models could have the same model layers and hyperparameters. It can be trained in parallel to speed up the training process. During the deep learning model training process, these features reduce the difficulties in adjusting sub-model parameters and the model training time cost. Meanwhile, this method is achieved by the local end-to-end training process. During the deep learning model predicting process, the increase in total prediction time cost can be ignored. The trained deep learning models can predict the optimized structures in real time. Maximization of first eigenfrequency topology optimization problem with three constraint conditions is used to verify the effectiveness of the proposed training method. The method proposed in this study provides an implementation technology for the real-time TO of structures. The authors also provide the deep learning model code and the dataset in this manuscript (git-hub)

Approximate Controllability for a Kind of Fractional Neutral Differential Equations with Damping

This paper gains several meaningful results on the mild solutions and approximate controllability for a kind of fractional neutral differential equations with damping (FNDED) and order belonging to 1,2 in Banach spaces. At first, a new expression for the mild solutions of FNDED via the (p, q)-regularized operator family and the technique of Laplace transform is acquired. Then, we consider the approximate controllability of FNDED by means of the approximate sequence method, and simultaneously, some applicable sufficient conditions are obtained

Problems with the application of heptane and isoheptane values as light hydrocarbon parameters

The light hydrocarbon data from 772 oil samples in 25 oilfields, together with GC/MS data from 338 saturated hydrocarbon samples were used to discuss the relationship between kerogen types, using the heptane value, isoheptane value and C29 sterane 20S/(S+R) ratio. Although the heptane and isoheptane values are related to kerogen type, the correlation is different from that in Thompson's interpretation, so the correlation cannot be directly used in research on land facies oils in China. Consideration should be taken when using the heptane and isoheptane values, as secondary alteration and mixed oil sources are the main factors leading to the abnormal change in heptane and isoheptane values. The heptane and isoheptane values have a larger maturity range than that of C29 sterane 20S/(S+R). There are three types of oil samples (original immature oil, altered oil and mixed source oil with different maturity) that may fall into the “Biodegradation” area of the Thompson interpretation. For the biodegraded oil in Thompson's interpretation, the reservoir may have undergone a secondary charge. 摘要: 用采自中国国内25个油区的772个原油轻烃分析数据, 结合其中338个样品的饱和烃GC/MS分析数据, 就原油正、异庚烷值与烃源岩干酪根类型的关系以及与C29甾20S/ (20S+20R)成熟度参数的相关性, 对影响参数值发生异常变化的因素等作了研讨。研究认为, 正、异庚烷值确实与母源干酪根类型有关, 但相关关系与Thompson的图版有所差别, 研究中国陆相原油时不宜直接引用; 原油次生蚀变和混源是使原油正、异庚烷值发生异常变化的重要因素, 在用正、异庚烷值作研究时必须备加注意; 正、异庚烷值标示原油成熟度的范围大于C29甾20S/(20S+20R)所能标示的; 落入Thompson图版“Biodegraded”区域的油样可能有3类: 原生的未熟油, 已遭蚀变的原油和成熟度不同的混源油, 对于未落入该区域内的生物降解油, 认为油藏存在二次注入的可能性。图6表2参26 Key words: light hydrocarbon, heptane value, isoheptane value, maturity parameter, secondary alteration, mixed source oi